Articoli correlati a Visualization and Imputation of Missing Values: With...
- EditoreSpringer Nature
- Data di pubblicazione2023
- ISBN 10 3031300726
- ISBN 13 9783031300721
- RilegaturaCopertina rigida
- LinguaInglese
- Numero edizione1
- Numero di pagine484
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Visualization and Imputation of Missing Values
Editore:
Springer, Berlin|Springer International Publishing|Springer, 2023
ISBN 10: 3031300726
ISBN 13: 9783031300721
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Da: moluna, Greven, Germania
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Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book explores visualization and imputation techniques for missing values and presents practical applications using the statistical software R. It explains the concepts of common imputation methods with a focus on visualization, description of data p. Codice articolo 829430233
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Visualization and Imputation of Missing Values
Editore:
Berlin Springer International Publishing Springer Sep 2023, 2023
ISBN 10: 3031300726
ISBN 13: 9783031300721
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book explores visualization and imputation techniques for missing values and presents practical applications using the statistical software R. It explains the concepts of common imputation methods with a focus on visualization, description of data problems and practical solutions using R, including modern methods of robust imputation, imputation based on deep learning and imputation for complex data. By describing the advantages, disadvantages and pitfalls of each method, the book presents a clear picture of which imputation methods are applicable given a specific data set at hand.The material covered includes the pre-analysis of data, visualization of missing values in incomplete data, single and multiple imputation, deductive imputation and outlier replacement, model-based methods including methods based on robust estimates, non-linear methods such as tree-based and deep learning methods, imputation of compositional data, imputation quality evaluation from visual diagnostics to precision measures, coverage rates and prediction performance and a description of different model- and design-based simulation designs for the evaluation. The book also features a topic-focused introduction to R and R code is provided in each chapter to explain the practical application of the described methodology. Addressed to researchers, practitioners and students who work with incomplete data, the book offers an introduction to the subject as well as a discussion of recent developments in the field. It is suitable for beginners to the topic and advanced readers alike. 460 pp. Englisch. Codice articolo 9783031300721
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Visualization and Imputation of Missing Values : With Applications in R
Editore:
Springer International Publishing, 2023
ISBN 10: 3031300726
ISBN 13: 9783031300721
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book explores visualization and imputation techniques for missing values and presents practical applications using the statistical software R. It explains the concepts of common imputation methods with a focus on visualization, description of data problems and practical solutions using R, including modern methods of robust imputation, imputation based on deep learning and imputation for complex data. By describing the advantages, disadvantages and pitfalls of each method, the book presents a clear picture of which imputation methods are applicable given a specific data set at hand.The material covered includes the pre-analysis of data, visualization of missing values in incomplete data, single and multiple imputation, deductive imputation and outlier replacement, model-based methods including methods based on robust estimates, non-linear methods such as tree-based and deep learning methods, imputation of compositional data, imputation quality evaluation from visual diagnostics to precision measures, coverage rates and prediction performance and a description of different model- and design-based simulation designs for the evaluation. The book also features a topic-focused introduction to R and R code is provided in each chapter to explain the practical application of the described methodology. Addressed to researchers, practitioners and students who work with incomplete data, the book offers an introduction to the subject as well as a discussion of recent developments in the field. It is suitable for beginners to the topic and advanced readers alike. Codice articolo 9783031300721
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Visualization and Imputation of Missing Values : With Applications in R
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Condizione: As New. Unread book in perfect condition. Codice articolo 46235598
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Visualization and Imputation of Missing Values : With Applications in R
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Condizione: As New. Unread book in perfect condition. Codice articolo 46235598
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Visualization and Imputation of Missing Values: With Applications in R (Statistics and Computing)
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Condizione: New. In. Codice articolo ria9783031300721_new
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Visualization and Imputation of Missing Values : With Applications in R
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Visualization and Imputation of Missing Values: With Applications in R (Statistics and Computing)
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Condizione: New. Codice articolo I-9783031300721
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Visualization and Imputation of Missing Values : With Applications in R
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Visualization and Imputation of Missing Values (Hardcover)
Editore:
Springer International Publishing AG, Cham, 2023
ISBN 10: 3031300726
ISBN 13: 9783031300721
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Hardcover. Condizione: new. Hardcover. This book explores visualization and imputation techniques for missing values and presents practical applications using the statistical software R. It explains the concepts of common imputation methods with a focus on visualization, description of data problems and practical solutions using R, including modern methods of robust imputation, imputation based on deep learning and imputation for complex data. By describing the advantages, disadvantages and pitfalls of each method, the book presents a clear picture of which imputation methods are applicable given a specific data set at hand.The material covered includes the pre-analysis of data, visualization of missing values in incomplete data, single and multiple imputation, deductive imputation and outlier replacement, model-based methods including methods based on robust estimates, non-linear methods such as tree-based and deep learning methods, imputation of compositional data, imputation quality evaluation from visual diagnostics to precision measures, coverage rates and prediction performance and a description of different model- and design-based simulation designs for the evaluation. The book also features a topic-focused introduction to R and R code is provided in each chapter to explain the practical application of the described methodology. Addressed to researchers, practitioners and students who work with incomplete data, the book offers an introduction to the subject as well as a discussion of recent developments in the field. It is suitable for beginners to the topic and advanced readers alike. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9783031300721
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